US9666201B2 - Bandwidth extension method and apparatus using high frequency excitation signal and high frequency energy - Google Patents

Bandwidth extension method and apparatus using high frequency excitation signal and high frequency energy Download PDF

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US9666201B2
US9666201B2 US15/068,908 US201615068908A US9666201B2 US 9666201 B2 US9666201 B2 US 9666201B2 US 201615068908 A US201615068908 A US 201615068908A US 9666201 B2 US9666201 B2 US 9666201B2
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frequency
signal
excitation signal
high frequency
factor
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US20160196829A1 (en
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Zexin LIU
Lei Miao
Bin Wang
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Top Quality Telephony LLC
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Huawei Technologies Co Ltd
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • G10L19/087—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters using mixed excitation models, e.g. MELP, MBE, split band LPC or HVXC
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/005—Correction of errors induced by the transmission channel, if related to the coding algorithm
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/06—Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • G10L19/12—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters the excitation function being a code excitation, e.g. in code excited linear prediction [CELP] vocoders
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/038—Speech enhancement, e.g. noise reduction or echo cancellation using band spreading techniques
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/038—Speech enhancement, e.g. noise reduction or echo cancellation using band spreading techniques
    • G10L21/0388—Details of processing therefor
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/90—Pitch determination of speech signals
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L2019/0001—Codebooks
    • G10L2019/0002—Codebook adaptations
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/90—Pitch determination of speech signals
    • G10L2025/906—Pitch tracking

Definitions

  • the present invention relates to the field of audio encoding and decoding, and in particular, to a bandwidth extension method and apparatus in an algebraic code excited linear prediction (ACELP) of a medium and low rate wideband.
  • ACELP algebraic code excited linear prediction
  • a blind bandwidth extension technology is a technology at a decoder, and a decoder performs blind bandwidth extension according to a low-frequency decoding signal and by using a corresponding prediction method.
  • the present invention provides a bandwidth extension method and apparatus, and aims at solving a problem that a high frequency band signal recovered by using an existing blind bandwidth extension technology deviates much from an original high frequency band signal.
  • a bandwidth extension method including: acquiring a bandwidth extension parameter, where the bandwidth extension parameter includes one or more of the following parameters: a linear predictive coefficient (LPC), a line spectral frequency (LSF) parameter, a pitch period, a decoding rate, an adaptive codebook contribution, and an algebraic codebook contribution; and performing, according to the bandwidth extension parameter, bandwidth extension on a decoded low-frequency signal, to obtain a high frequency band signal.
  • LPC linear predictive coefficient
  • LSF line spectral frequency
  • the performing, according to the bandwidth extension parameter, bandwidth extension on a decoded low-frequency signal, to obtain a high frequency band signal includes: predicting high-frequency energy and a high band excitation signal according to the bandwidth extension parameter; and obtaining the high frequency band signal according to the high-frequency energy and the high band excitation signal.
  • the high-frequency energy includes a high-frequency gain
  • the predicting high-frequency energy and a high band excitation signal according to the bandwidth extension parameter includes: predicting the high-frequency gain according to the LPC; and adaptively predicting the high band excitation signal according to the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the adaptively predicting the high band excitation signal according to the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution includes: adaptively predicting the high band excitation signal according to the decoding rate, the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the predicting high-frequency energy and a high band excitation signal according to the bandwidth extension parameter includes: predicting the high-frequency gain according to the LPC; and adaptively predicting the high band excitation signal according to the adaptive codebook contribution and the algebraic codebook contribution.
  • the adaptively predicting the high band excitation signal according to the adaptive codebook contribution and the algebraic codebook contribution includes: adaptively predicting the high band excitation signal according to the decoding rate, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency envelope
  • the predicting high-frequency energy and a high band excitation signal according to the bandwidth extension parameter includes: predicting the high-frequency envelope according to the decoded low-frequency signal or a low-frequency excitation signal, where the low-frequency excitation signal is the sum of the adaptive codebook contribution and the algebraic codebook contribution; and predicting the high band excitation signal according to the decoded low-frequency signal or the low-frequency excitation signal.
  • the predicting the high band excitation signal according to the decoded low-frequency signal or the low-frequency excitation signal includes: predicting the high band excitation signal according to the decoding rate and the decoded low-frequency signal.
  • the predicting the high band excitation signal according to the decoded low-frequency signal or a low-frequency excitation signal includes: predicting the high band excitation signal according to the decoding rate and the low-frequency excitation signal.
  • the method further includes: determining a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the first correction factor includes one or more of the following parameters: a voicing factor, a noise gate factor, and a spectrum tilt factor; and correcting the high-frequency energy according to the first correction factor.
  • the determining a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal includes: determining the first correction factor according to the pitch period, the adaptive codebook contribution, the algebraic codebook contribution, and the decoded low-frequency signal.
  • the determining a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal includes: determining the first correction factor according to the decoded low-frequency signal.
  • the determining a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal includes: determining the first correction factor according to the pitch period, the adaptive codebook contribution, the algebraic codebook contribution, and the decoded low-frequency signal.
  • the method further includes: correcting the high-frequency energy according to the pitch period.
  • the method further includes: determining a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the second correction factor includes at least one of a classification parameter and a signal type; and correcting the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the determining a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal includes: determining the second correction factor according to the bandwidth extension parameter.
  • the determining a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal includes: determining the second correction factor according to the decoded low-frequency signal.
  • the determining a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal includes: determining the second correction factor according to the bandwidth extension parameter and the decoded low-frequency signal.
  • the method further includes: weighting the predicted high band excitation signal and a random noise signal, to obtain a final high band excitation signal, where a weight of the weighting is determined according to a value of a classification parameter and/or a voicing factor of the decoded low-frequency signal.
  • the obtaining the high frequency band signal according to the high-frequency energy and the high band excitation signal includes: synthesizing the high-frequency energy and the high band excitation signal, to obtain the high frequency band signal; or synthesizing the high-frequency energy, the high band excitation signal, and a predicted LPC, to obtain the high frequency band signal, where the predicted LPC includes a predicted high frequency band LPC or a predicted wideband LPC, and the predicted LPC is obtained based on the LPC.
  • a bandwidth extension apparatus including: an acquisition unit, configured to acquire a bandwidth extension parameter, where the bandwidth extension parameter includes one or more of the following parameters: a linear predictive coefficient (LPC), a line spectral frequency (LSF) parameter, a pitch period, a decoding rate, an adaptive codebook contribution, and an algebraic codebook contribution; and a bandwidth extension unit, configured to perform, according to the bandwidth extension parameter acquired by the acquisition unit, bandwidth extension on a decoded low-frequency signal, to obtain a high frequency band signal.
  • LPC linear predictive coefficient
  • LSF line spectral frequency
  • the bandwidth extension unit includes: a prediction subunit, configured to predict high-frequency energy and a high band excitation signal according to the bandwidth extension parameter; and a synthesis subunit, configured to obtain the high frequency band signal according to the high-frequency energy and the high band excitation signal.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit is specifically configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit is specifically configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the decoding rate, the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit is specifically configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the adaptive codebook contribution and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit is specifically configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the decoding rate, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency envelope; and the prediction subunit is specifically configured to: predict the high-frequency envelope according to the decoded low-frequency signal; and predict the high band excitation signal according to the decoded low-frequency signal or a low-frequency excitation signal, where the low-frequency excitation signal is the sum of the adaptive codebook contribution and the algebraic codebook contribution.
  • the prediction subunit is specifically configured to: predict the high-frequency envelope according to the decoded low-frequency signal; and predict the high band excitation signal according to the decoding rate and the low-frequency excitation signal.
  • the prediction subunit is specifically configured to: predict the high-frequency envelope according to the decoded low-frequency signal; and predict the high band excitation signal according to the decoding rate and the decoded low-frequency signal.
  • the bandwidth extension unit further includes: a first correction subunit, configured to: after the high-frequency energy and the high band excitation signal are predicted according to the bandwidth extension parameter, determine a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the first correction factor includes one or more of the following parameters: a voicing factor, a noise gate factor, and a spectrum tilt factor; and correct the high-frequency energy according to the first correction factor.
  • a first correction subunit configured to: after the high-frequency energy and the high band excitation signal are predicted according to the bandwidth extension parameter, determine a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the first correction factor includes one or more of the following parameters: a voicing factor, a noise gate factor, and a spectrum tilt factor; and correct the high-frequency energy according to the first correction factor.
  • the first correction subunit is specifically configured to: determine the first correction factor according to the pitch period, the adaptive codebook contribution, and the algebraic codebook contribution; and correct the high-frequency energy according to the first correction factor.
  • the first correction subunit is specifically configured to: determine the first correction factor according to the decoded low-frequency signal; and correct the high-frequency energy according to the first correction factor.
  • the first correction subunit is specifically configured to: determine the first correction factor according to the pitch period, the adaptive codebook contribution, the algebraic codebook contribution, and the decoded low-frequency signal; and correct the high-frequency energy according to the first correction factor.
  • the bandwidth extension unit further includes: a second correction subunit, configured to correct the high-frequency energy according to the pitch period.
  • the bandwidth extension unit further includes: a third correction subunit, configured to determine a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the second correction factor includes at least one of a classification parameter and a signal type; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • a third correction subunit configured to determine a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the second correction factor includes at least one of a classification parameter and a signal type; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the third correction subunit is specifically configured to determine the second correction factor according to the bandwidth extension parameter; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the third correction subunit is specifically configured to determine the second correction factor according to the decoded low-frequency signal; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the third correction subunit is specifically configured to determine the second correction factor according to the bandwidth extension parameter and the decoded low-frequency signal; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the bandwidth extension unit further includes: a weighting subunit, configured to weight the predicted high band excitation signal and a random noise signal, to obtain a final high band excitation signal, where a weight of the weighting is determined according to a value of a classification parameter and/or a voicing factor of the decoded low-frequency signal.
  • the synthesis subunit is specifically configured to: synthesize the high-frequency energy and the high band excitation signal, to obtain the high frequency band signal; or synthesize the high-frequency energy, the high band excitation signal, and a predicted LPC, to obtain the high frequency band signal, where the predicted LPC includes a predicted high frequency band LPC or a predicted wideband LPC, and the predicted LPC is obtained based on the LPC.
  • bandwidth extension is performed, by using a bandwidth extension parameter and by using the bandwidth extension parameter, on a decoded low-frequency signal, thereby recovering a high frequency band signal.
  • the high frequency band signal recovered by using the bandwidth extension method and apparatus in the embodiments of the present invention is close to an original high frequency band signal, and the quality is satisfactory.
  • FIG. 1 is a flowchart of a bandwidth extension method according to an embodiment of the present invention
  • FIG. 2 is a block diagram of an implementation of a bandwidth extension method according to an embodiment of the present invention.
  • FIG. 4 is a block diagram of an implementation of a bandwidth extension method in a frequency domain according to an embodiment of the present invention
  • FIG. 5 is a block diagram of an implementation of a bandwidth extension method in a time domain according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of a bandwidth extension apparatus according to an embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of a bandwidth extension unit in a bandwidth extension apparatus according to an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of a bandwidth extension unit in a bandwidth extension apparatus according to another embodiment of the present invention.
  • FIG. 9 is a schematic structural diagram of a bandwidth extension unit in a bandwidth extension apparatus according to another embodiment of the present invention.
  • FIG. 10 is a schematic structural diagram of a bandwidth extension unit in a bandwidth extension apparatus according to another embodiment of the present invention.
  • FIG. 11 is a schematic structural diagram of a bandwidth extension unit in a bandwidth extension apparatus according to another embodiment of the present invention.
  • FIG. 12 is a schematic structural diagram of a decoder according to an embodiment of the present invention.
  • bandwidth extension is performed on a low-frequency signal according to any one of or a combination of some of a decoding rate, an LPC coefficient (an LSF parameter) and a pitch period that are obtained by directly decoding a code stream, an adaptive codebook contribution and an algebraic codebook contribution that are obtained by intermediate decoding, and a low-frequency signal obtained by final decoding, thereby recovering a high frequency band signal.
  • a decoder acquires a bandwidth extension parameter, where the bandwidth extension parameter includes one or more of the following parameters: a linear predictive coefficient (LPC), a line spectral frequency (LSF) parameter, a pitch period, an adaptive codebook contribution, and an algebraic codebook contribution.
  • LPC linear predictive coefficient
  • LSF line spectral frequency
  • the decoder may be disposed in a hardware device such as a mobile phone, a tablet, a computer, a television set, a set top box, or a gaming console on which a decoding operation needs to be performed, and work under the control of processors in these hardware devices.
  • the decoder may also be an independent hardware device, where the hardware device includes a processor, and the hardware device works under the control of the processor.
  • the LPC is a coefficient of a linear prediction filter
  • the linear prediction filter can describe a basic feature of a sound channel model
  • the LPC also reflects an energy change trend of a signal in a frequency domain
  • the LSF parameter is a representation manner of the frequency domain of the LPC.
  • an airflow passes through a glottis, and makes vocal cords produce a relaxation oscillatory vibration, thereby creating a quasi-periodic pulse airflow.
  • This airflow excites a sound channel and then the voiced sound is produced, which is also referred to as a voiced speech.
  • the voiced speech carries most energy in a speech.
  • a fundamental frequency Such a frequency at which the vocal cords vibrate is referred to as a fundamental frequency, and a corresponding period is referred to as the pitch period.
  • the decoding rate refers to that, in a speech encoding algorithm, encoding and decoding are both processed according to a rate (a bit rate) that is set in advance, and for different decoding rates, processing manners or parameters may be different.
  • the adaptive codebook contribution is a quasi-periodic portion in a residual signal after a speech signal is analyzed by using the LPC.
  • the algebraic codebook contribution refers to a quasi-noise portion in the residual signal after the speech signal is analyzed by using the LPC.
  • the LPC and the LSF parameter may be obtained by directly decoding the code stream; the adaptive codebook contribution and the algebraic codebook contribution may be combined to obtain a low-frequency excitation signal.
  • the adaptive codebook contribution reflects a quasi-periodic constituent of the signal
  • the algebraic codebook contribution reflects a quasi-noise constituent of the signal.
  • the decoder performs, according to the bandwidth extension parameter, bandwidth extension on a decoded low-frequency signal, to obtain a high frequency band signal.
  • high-frequency energy and a high band excitation signal are predicted according to the bandwidth extension parameter, where the high-frequency energy may include a high-frequency envelope or a high-frequency gain; then, the high frequency band signal is obtained according to the high-frequency energy and the high band excitation signal.
  • the bandwidth extension parameter involved in the prediction of the high-frequency energy or the high band excitation signal may be different.
  • the predicting high-frequency energy and a high band excitation signal according to the bandwidth extension parameter may include: predicting the high-frequency gain according to the LPC; and adaptively predicting the high band excitation signal according to the LSF parameter, the adaptive codebook contribution and the algebraic codebook contribution. Further, the high band excitation signal may be further adaptively predicted according to the decoding rate, the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the predicting high-frequency energy and a high band excitation signal according to the bandwidth extension parameter may include: predicting the high-frequency gain according to the LPC; and adaptively predicting the high band excitation signal according to the adaptive codebook contribution and the algebraic codebook contribution. Further, the high band excitation signal may be further adaptively predicted according to the decoding rate, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the bandwidth extension method in this embodiment of the present invention may further include: determining a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the first correction factor includes one or more of the following parameters: a voicing factor, a noise gate factor, and a spectrum tilt factor; and correcting the high-frequency energy according to the first correction factor.
  • the voicing factor or the noise gate factor may be determined according to the bandwidth extension parameter
  • the spectrum tilt factor may be determined according to the decoded low-frequency signal.
  • the determining a first correction factor according to the bandwidth extension parameter and the decoded low-frequency signal may include: determining the first correction factor according to the decoded low-frequency signal; or, determining the first correction factor according to the pitch period, the adaptive codebook contribution, and the algebraic codebook contribution; or, determining the first correction factor according to the pitch period, the adaptive codebook contribution, the algebraic codebook contribution, and the decoded low-frequency signal.
  • the bandwidth extension method in this embodiment of the present invention may further include: correcting the high-frequency energy according to the pitch period.
  • the bandwidth extension method in this embodiment of the present invention may further include: determining a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the second correction factor includes at least one of a classification parameter and a signal type; and correcting the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the determining a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal may include: determining the second correction factor according to the bandwidth extension parameter; or, determining the second correction factor according to the decoded low-frequency signal; or, determining the second correction factor according to the bandwidth extension parameter and the decoded low-frequency signal.
  • the bandwidth extension method in this embodiment of the present invention may further include: correcting the high band excitation signal according to a random noise signal and the decoding rate.
  • the obtaining the high frequency band signal according to the high-frequency energy and the high band excitation signal may include: synthesizing the high-frequency energy and the high band excitation signal, to obtain the high frequency band signal; or synthesizing the high-frequency energy, the high band excitation signal, and a predicted LPC, to obtain the high frequency band signal, where the predicted LPC includes a predicted high frequency band LPC or a predicted wideband LPC, and the predicted LPC is obtained based on the LPC.
  • the “wideband” in the wideband LPC herein includes a low frequency band and a high frequency band.
  • bandwidth extension is performed, by using a bandwidth extension parameter, on a decoded low-frequency signal, thereby recovering a high frequency band signal.
  • the high frequency band signal recovered by using the bandwidth extension method in this embodiment of the present invention is close to an original high frequency band signal, and the quality is satisfactory.
  • high-frequency energy is predicted by fully using a low-frequency parameter obtained by directly decoding a code stream, a intermediate decoded parameter, or the low-frequency signal obtained by final decoding; a high band excitation signal is adaptively predicted according to a low-frequency excitation signal, so that the high frequency band signal that is finally output is closer to the original high frequency band signal, thereby improving quality of the output signal.
  • FIG. 2 shows a schematic flowchart of a bandwidth extension method according to a specific embodiment of the present invention.
  • any one of or a combination of some of a voicing factor, a noise gate factor, a spectrum tilt factor, and a value of a classification parameter is calculated according to any one of or a combination of some of a decoding rate, an LPC (or an LSF parameter) and a pitch period that are obtained by directly decoding a code stream, parameters such as an adaptive codebook contribution and an algebraic codebook contribution that are obtained by intermediate decoding, and a low-frequency signal obtained by final decoding.
  • the voicing factor is a ratio of the adaptive codebook contribution to the algebraic codebook contribution
  • the noise gate factor is a parameter used to represent magnitude of a signal background noise
  • the spectrum tilt factor is used to represent a degree of signal spectrum tilt or an energy change trend of a signal between different frequency bands, where the classification parameter is a parameter used to differentiate signal types.
  • the high frequency band LPC or the wideband LPC may be predicted according to the LPC obtained by decoding.
  • the high-frequency envelope or the high-frequency gain may be predicted in the following manner:
  • the high-frequency gain or the high-frequency envelope is predicted by using the predicted LPC and the LPC obtained by decoding, or a relationship between high and low frequencies of the decoded low-frequency signal.
  • different correction factors are calculated to correct the predicted high-frequency gain or high-frequency envelope.
  • the predicted high-frequency envelope or high-frequency gain may be corrected by using a weighted value or weighted values of any one or some of the classification parameter, the spectrum tilt factor, the voicing factor, and the noise gate factor of the decoded low-frequency signal.
  • the predicted high-frequency envelope may be further corrected by using the pitch period.
  • high band excitation signals are predicted by adaptively selecting low-frequency signals with different frequency bands and obtained by decoding, or by using different prediction algorithms.
  • the predicted high band excitation signal and a random noise signal are weighted, to obtain a final high band excitation signal, where a weight is determined according to the value of the classification parameter and/or the voicing factor of the decoded low-frequency signal.
  • the high frequency band signal is synthesized by using the predicted high-frequency energy and high band excitation signal, or by using the predicted high-frequency energy and high band excitation signal, and the predicted LPC.
  • high-frequency energy is predicted by fully using a low-frequency parameter obtained by directly decoding a code stream, an intermediate decoded parameter, or a low-frequency signal obtained by final decoding; a high band excitation signal is adaptively predicted according to a low-frequency excitation signal, so that a high frequency band signal that is finally output is closer to an original high frequency band signal, thereby improving quality of the output signal.
  • a specific implementation process of the bandwidth extension method in this embodiment of the present invention may vary.
  • a wideband LPC is predicted according to an LPC obtained by decoding.
  • a high-frequency gain is predicted by using a relationship between the predicted wideband LPC and the LPC obtained by decoding.
  • different correction factors are calculated to correct the predicted high-frequency gain.
  • the predicted high-frequency gain is corrected by using a classification parameter, a spectrum tilt factor, a voicing factor, and a noise gate factor of a decoded low-frequency signal.
  • a corrected high-frequency gain is proportional to a minimum noise gate factor ng_min, proportional to a value (merit of the classification parameter, proportional to an opposite number of the spectrum tilt factor tilt, and inversely proportional to the voicing factor voice_fac.
  • a larger high-frequency gain indicates a smaller spectrum tilt factor; a louder background noise indicates a larger noise gate factor; a stronger speech characteristic indicates a larger value of the classification parameter.
  • the corrected high-frequency gain gain*(1 ⁇ tilt)*fmerit*(30+ng_min)*(1.6 ⁇ voice_fac).
  • a noise gate factor evaluated in each frame needs to be compared with a given threshold; therefore, when the noise gate factor evaluated in each frame is less than the given threshold, the minimum noise gate factor is equal to the noise gate factor evaluated in each frame; otherwise, the minimum noise gate factor is equal to the given threshold.
  • high band excitation signals are predicted by adaptively selecting low-frequency signals with different frequency bands and obtained by decoding, or by using different prediction algorithms. For example, when a decoding rate is greater than a given value, a low-frequency excitation signal (the sum of the adaptive codebook contribution and the algebraic codebook contribution) with a frequency band adjacent to the high frequency band signal is used as the high band excitation signal; otherwise, a signal with a frequency band whose encoding quality is better (that is, a difference value between LSF parameters is smaller) is adaptively selected from low-frequency excitation signals as the high band excitation signal by using the difference value between the LSF parameters. It may be understood that, different decoders may select different given values.
  • an adaptive multi-rate wideband (AMR-WB) codec supports decoding rates such as 12.65 kbps, 15.85 kbps, 18.25 kbps, 19.85 kbps, 23.05 kbps, and 23.85 kbps, and then the AMR-WB codec may select 19.85 kbps as the given value.
  • AMR-WB codec supports decoding rates such as 12.65 kbps, 15.85 kbps, 18.25 kbps, 19.85 kbps, 23.05 kbps, and 23.85 kbps, and then the AMR-WB codec may select 19.85 kbps as the given value.
  • An ISF parameter (the ISF parameter is a group of numbers, and is the same as an order of an LPC coefficient) is a representation manner of a frequency domain of the LPC coefficient, and reflects an energy change of a speech/audio signal in the frequency domain.
  • a value of the ISF roughly corresponds to an entire frequency band from a low frequency to a high frequency of the speech/audio signal, and each value of the ISF parameter corresponds to one corresponding frequency value.
  • a signal with a frequency band whose encoding quality is better (that is, a difference value between LSF parameters is smaller) is adaptively selected from low-frequency excitation signals as the high band excitation signal by using the difference value between the LSF parameters
  • a difference value between each two LSF parameters is calculated, to obtain a group of difference values of the LSF parameters; a minimum difference value is searched for, and a frequency bin corresponding to the LSF parameter is determined according to the minimum difference value; and a frequency domain excitation signal with a frequency band is selected from frequency domain excitation signals according to the frequency bin, and is used as an excitation signal with a high frequency band.
  • a different minimum start selection frequency bin is selected.
  • the selection may be performed adaptively from a range of 2 to 6 kHz; for the music signal, the selection may be performed adaptively from a range of 1 to 6 kHz.
  • exc[n] is the predicted high band excitation signal
  • random[n] is the random noise signal
  • ⁇ is a weight of the predicted high band excitation signal
  • ⁇ is a weight of the random noise signal
  • ⁇ is a value that is preset when the weight of the predicted high band excitation signal is calculated to be ⁇
  • fmerit is the value of the classification parameter
  • voice_fac is the voicing factor.
  • signals classification methods are different, and therefore high band excitation signals are predicted by adaptively selecting low-frequency signals with different frequency bands and obtained by decoding or by using different prediction algorithms.
  • signals may be classified into speech signals and music signals, where the speech signals may be further classified into unvoiced sounds, voiced sounds, and transition sounds.
  • the signals may be further classified into transient signals and non-transient signals, and so on.
  • the high frequency band signal is synthesized by using the predicted high-frequency gain and high band excitation signal, and the predicted LPC.
  • the high band excitation signal is corrected by using the predicted high-frequency gain, and then a corrected high band excitation signal passes through an LPC synthesis filter, to obtain a high frequency band signal that is finally output; or the high band excitation signal passes through an LPC synthesis filter, to obtain a high frequency band signal, and then the high frequency band signal is corrected by using the high-frequency gain, to obtain a high frequency band signal that is finally output.
  • the LPC synthesis filter is a linear filter, and therefore a correction before the synthesis is the same as a correction after the synthesis.
  • a result of correcting the high band excitation signal before the synthesis by using the high-frequency gain is the same as a result of correcting the high band excitation signal after the synthesis by using the high-frequency gain, and therefore there is no sequential order for correction.
  • the obtained high band excitation signal of the frequency domain is converted into the high band excitation signal of the time domain, the high band excitation signal of the time domain and the high-frequency gain of the time domain are used as inputs of the synthesis filter, and the predicted LPC coefficient is used as a coefficient of the synthesis filter, thereby obtaining the synthesized high frequency band signal.
  • high-frequency energy is predicted by fully using a low-frequency parameter obtained by directly decoding a code stream, a intermediate decoded parameter, or a low-frequency signal obtained by final decoding; a high band excitation signal is adaptively predicted according to a low-frequency excitation signal, so that a high frequency band signal that is finally output is closer to an original high frequency band signal, thereby improving quality of the output signal.
  • a high frequency band LPC is predicted according to an LPC obtained by decoding.
  • a high frequency band signal that needs to be extended is divided into M sub-bands, and high-frequency envelopes of the M sub-bands are predicted.
  • N frequency bands adjacent to the high frequency band signal are selected from a decoded low-frequency signal, energy or amplitude of the N frequency bands is calculated, and the high-frequency envelopes of the M sub-bands are predicted according to a size relationship between the energy or the amplitude of the N frequency bands.
  • M and N are both preset values.
  • the predicted high-frequency envelopes are corrected by using a classification parameter of the decoded low-frequency signal, a pitch period, an energy or amplitude ratio between high and low frequencies of the low-frequency signal, a voicing factor, and a noise gate factor.
  • high frequencies and low frequencies may be divided differently for different low-frequency signals. For example, if bandwidth of a low-frequency signal is 6 kHz, 0 to 3 kHz and 3 to 6 kHz may be respectively used as low frequencies and high frequencies of the low-frequency signal, or 0 to 4 kHz and 4 to 6 kHz may be respectively used as low frequencies and high frequencies of the low-frequency signal.
  • a corrected high-frequency envelope is proportional to a minimum noise gate factor ng_min, proportional to a value fmerit of the classification parameter, proportional to an opposite number of a spectrum tilt factor tilt, and inversely proportional to the voicing factor voice_fac.
  • a corrected high-frequency envelope is proportional to the pitch period.
  • larger high-frequency energy indicates a smaller spectrum tilt factor
  • a louder background noise indicates a larger noise gate factor
  • a stronger speech characteristic indicates a larger value of the classification parameter.
  • the corrected high-frequency envelope gain* (1 ⁇ tilt)*fmerit*(30+ng_min)*(1.6 ⁇ voice_fac)*(pitch/100).
  • a frequency band, of a low-frequency signal, adjacent to the high frequency band signal is selected to predict a high band excitation signal; or, when a decoding rate is less than a given threshold, a sub-band whose encoding quality is better is adaptively selected to predict a high band excitation signal.
  • the given threshold may be an empirical value.
  • the predicted high band excitation signal is weighted by using a random noise signal, and a weighted value is determined by the classification parameter of the low-frequency signal.
  • exc[n] is the predicted high band excitation signal
  • random[n] is the random noise signal
  • ⁇ is a weight of the predicted high band excitation signal
  • ⁇ is the weight of the random noise signal
  • ⁇ is a value that is preset when the weight of the predicted high band excitation signal is calculated to be ⁇
  • fmerit is a value of the classification parameter.
  • the high frequency band signal is synthesized by using the predicted high-frequency envelope and high band excitation signal.
  • a synthesis process may be directly multiplying the high band excitation signal of the frequency domain by the high-frequency envelope of the frequency domain, to obtain the synthesized high frequency band signal.
  • high-frequency energy is predicted by fully using a low-frequency parameter obtained by directly decoding a code stream, a intermediate decoded parameter, or a low-frequency signal obtained by final decoding; a high band excitation signal is adaptively predicted according to a low-frequency excitation signal, so that a high frequency band signal that is finally output is closer to an original high frequency band signal, thereby improving quality of the output signal.
  • a wideband LPC is predicted according to an LPC obtained by decoding.
  • a high frequency band signal that needs to be extended is divided into M subframes, and high-frequency gains of the M subframes are predicted by using a relationship between the predicted wideband LPC and the LPC obtained by decoding.
  • a high-frequency gain of a current subframe is predicted by using a low-frequency signal or a low-frequency excitation signal of the current subframe or a current frame.
  • the predicted high-frequency gain is corrected by using a classification parameter of the decoded low-frequency signal, a pitch period, an energy or amplitude ratio between high and low frequencies of the low-frequency signal, a voicing factor, and a noise gate factor.
  • a corrected high-frequency gain is proportional to a minimum noise gate factor ng_min, proportional to a value fmerit of the classification parameter, proportional to an opposite number of a spectrum tilt factor tilt, and inversely proportional to the voicing factor voice_fac.
  • a corrected high-frequency gain is proportional to the pitch period.
  • the corrected high-frequency gain gain* (1 ⁇ tilt)*fmerit*(30+ng_min)*(1.6 ⁇ voice_fac)*(pitch/100),
  • tilt is the spectrum tilt factor
  • fmerit is the value of the classification parameter
  • ng_min is the minimum noise gate factor
  • voice_fac is the voicing factor
  • pitch is the pitch period.
  • a frequency band, of the decoded low-frequency signal, adjacent to the high frequency band signal is selected to predict a high band excitation signal; or, when a decoding rate is less than a given threshold, a frequency band whose encoding quality is better is adaptively selected to predict a high band excitation signal. That is, a low-frequency excitation signal (an adaptive codebook contribution and an algebraic codebook contribution) with a frequency band adjacent to the high frequency band signal may be used as the high band excitation signal.
  • the predicted high band excitation signal is weighted by using a random noise signal, and a weighted value is determined by the classification parameter of the low-frequency signal and a weighted value of the voicing factor.
  • the high frequency band signal is synthesized by using the predicted high-frequency gain and high band excitation signal, and the predicted LPC.
  • a synthesis process may be using the high band excitation signal of the time domain and the high-frequency gain of the time domain as inputs of a synthesis filter, and using the predicted LPC coefficient as a coefficient of the synthesis filter, thereby obtaining the synthesized high frequency band signal.
  • high-frequency energy is predicted by fully using a low-frequency parameter obtained by directly decoding a code stream, a intermediate decoded parameter, or a low-frequency signal obtained by final decoding; a high band excitation signal is adaptively predicted according to a low-frequency excitation signal, so that a high frequency band signal that is finally output is closer to an original high frequency band signal, thereby improving quality of the output signal.
  • FIG. 6 to FIG. 11 show structural diagrams of a bandwidth extension apparatus according to an embodiment of the present invention.
  • a bandwidth extension apparatus 60 includes an acquisition unit 61 and a bandwidth extension unit 62 .
  • the acquisition unit 61 is configured to acquire a bandwidth extension parameter, where the bandwidth extension parameter includes one or more of the following parameters: a linear predictive coefficient (LPC), a line spectral frequency (LSF) parameter, a pitch period, a decoding rate, an adaptive codebook contribution, and an algebraic codebook contribution.
  • LPC linear predictive coefficient
  • LSF line spectral frequency
  • the bandwidth extension unit 62 is configured to perform, according to the bandwidth extension parameter acquired by the acquisition unit 61 , bandwidth extension on a decoded low-frequency signal, to obtain a high frequency band signal.
  • the bandwidth extension unit 62 includes a prediction subunit 621 and a synthesis subunit 622 .
  • the prediction subunit 621 is configured to predict high-frequency energy and a high band excitation signal according to the bandwidth extension parameter.
  • the synthesis subunit 622 is configured to obtain the high frequency band signal according to the high-frequency energy and the high band excitation signal.
  • the synthesis subunit 622 is configured to: synthesize the high-frequency energy and the high band excitation signal, to obtain the high frequency band signal; or synthesize the high-frequency energy, the high band excitation signal, and a predicted LPC, to obtain the high frequency band signal, where the predicted LPC includes a predicted high frequency band LPC or a predicted wideband LPC, and the predicted LPC is obtained based on the LPC.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit 621 is configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit 621 is configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the decoding rate, the LSF parameter, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit 621 is configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the adaptive codebook contribution and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency gain
  • the prediction subunit 621 is configured to: predict the high-frequency gain according to the LPC; and adaptively predict the high band excitation signal according to the decoding rate, the adaptive codebook contribution, and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency envelope
  • the prediction subunit 621 is configured to: predict the high-frequency envelope according to the decoded low-frequency signal; and predict the high band excitation signal according to the decoded low-frequency signal or a low-frequency excitation signal, where the low-frequency excitation signal is the sum of the adaptive codebook contribution and the algebraic codebook contribution.
  • the high-frequency energy includes a high-frequency envelope
  • the prediction subunit 621 is configured to predict the high-frequency envelope according to the decoded low-frequency signal, and predict the high band excitation signal according to the decoding rate and the decoded low-frequency signal.
  • the high-frequency energy includes a high-frequency envelope
  • the prediction subunit 621 is configured to predict the high-frequency envelope according to the decoded low-frequency signal, and predict the high band excitation signal according to the decoding rate and the low-frequency excitation signal.
  • the bandwidth extension unit 62 further includes a first correction subunit 623 , as shown in FIG. 8 .
  • the first correction subunit 623 is configured to: after the high-frequency energy and the high band excitation signal are predicted according to the bandwidth extension parameter, determine a first correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal; and correct the high-frequency energy according to the first correction factor, where the first correction factor includes one or more of the following parameters: a voicing factor, a noise gate factor, and a spectrum tilt factor.
  • the first correction subunit 623 is configured to determine the first correction factor according to the pitch period, the adaptive codebook contribution, and the algebraic codebook contribution; and correct the high-frequency energy according to the first correction factor.
  • the first correction subunit is specifically configured to: determine the first correction factor according to the decoded low-frequency signal; and correct the high-frequency energy according to the first correction factor.
  • the first correction subunit is specifically configured to: determine the first correction factor according to the pitch period, the adaptive codebook contribution, the algebraic codebook contribution, and the decoded low-frequency signal; and correct the high-frequency energy according to the first correction factor.
  • the bandwidth extension unit 62 further includes a second correction subunit 624 , as shown in FIG. 9 , configured to correct the high-frequency energy according to the pitch period.
  • the bandwidth extension unit 62 further includes a third correction subunit 625 , as shown in FIG. 10 , configured to determine a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the second correction factor includes at least one of a classification parameter and a signal type; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • a third correction subunit 625 as shown in FIG. 10 , configured to determine a second correction factor according to at least one of the bandwidth extension parameter and the decoded low-frequency signal, where the second correction factor includes at least one of a classification parameter and a signal type; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the third correction subunit 625 is configured to determine the second correction factor according to the bandwidth extension parameter; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the third correction subunit 625 is configured to determine the second correction factor according to the decoded low-frequency signal; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the third correction subunit 625 is configured to determine the second correction factor according to the bandwidth extension parameter and the decoded low-frequency signal; and correct the high-frequency energy and the high band excitation signal according to the second correction factor.
  • the bandwidth extension unit 62 further includes a weighting subunit 626 , as shown in FIG. 11 , configured to weight the predicted high band excitation signal and a random noise signal, to obtain a final high band excitation signal, where a weight of the weighting is determined according to a value of a classification parameter and/or a voicing factor of the decoded low-frequency signal.
  • the bandwidth extension apparatus 60 may further include a processor, where the processor is configured to control units included in the bandwidth extension apparatus.
  • the bandwidth extension apparatus in this embodiment of the present invention predicts high-frequency energy by fully using a low-frequency parameter obtained by directly decoding a code stream, a intermediate decoded parameter, or a low-frequency signal obtained by final decoding; adaptively predicts a high band excitation signal according to a low-frequency excitation signal, so that a high frequency band signal that is finally output is closer to an original high frequency band signal, thereby improving quality of the output signal.
  • FIG. 12 shows a schematic structural diagram of a decoder 120 according to an embodiment of the present invention.
  • the decoder 120 includes a processor 121 and a memory 122 .
  • the processor 121 implements a bandwidth extension method in an embodiment of the present invention. That is, the processor 121 is configured to acquire a bandwidth extension parameter, where the bandwidth extension parameter includes one or more of the following parameters: a linear predictive coefficient (LPC), a line spectral frequency (LSF) parameter, a pitch period, a decoding rate, an adaptive codebook contribution, and an algebraic codebook contribution; and perform, according to the bandwidth extension parameter, bandwidth extension on a decoded low-frequency signal, to obtain a high frequency band signal.
  • LPC linear predictive coefficient
  • LSF line spectral frequency
  • the memory 122 is configured to store instructions to be executed by the processor 121 .
  • the disclosed system, apparatus, and method may be implemented in other manners.
  • the described apparatus embodiment is merely exemplary.
  • the unit division is merely logical function division and may be other division in actual implementation.
  • a plurality of units or components may be combined or integrated into another system, or some features may be ignored or not performed.
  • the displayed or discussed mutual couplings or direct couplings or communication connections may be implemented by using some interfaces.
  • the indirect couplings or communication connections between the apparatuses or units may be implemented in electronic, mechanical, or other forms.
  • the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • functional units in the embodiments of the present invention may be integrated into one processing unit, or each of the units may exist alone physically, or two or more units are integrated into one unit.
  • the functions When the functions are implemented in the form of a software functional unit and sold or used as an independent product, the functions may be stored in a computer-readable storage medium.
  • the computer software product is stored in a storage medium, and includes some instructions for instructing a computer device (which may be a personal computer, a server, or a network device) to perform all or some of the steps of the methods described in the embodiments of the present invention.
  • the foregoing storage medium includes: any medium that can store program code, such as a USB flash drive, a removable hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc.

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